Procedural sedation and analgesia in rural and regional emergency departments.
Bibliographic record
Abstract
INTRODUCTION: Several agents can be administered during procedural sedation and analgesia (PSA) in the emergency department (ED). The purpose of this study was to determine the PSA agents commonly used by physicians working in nontertiary EDs, and to assess the physicians' comfort level administering the agents as well as their knowledge of adverse effects of the agents. METHODS: We distributed a confidential electronic survey to physicians working in nontertiary EDs in southwestern Ontario. Using a 5-point Likert scale, ED physicians were asked to rate their use of older and newer agents used for PSA in the ED, as well as their familiarity with the agents. RESULTS: A total of 55 physicians completed the survey. The most frequently used drugs were fentanyl (66.0% often or always) and propofol with fentanyl (59.2% often or always). Most respondents stated that they rarely used ketofol (54.2% rarely or never) or etomidate (77.1% rarely or never). Respondents were most comfortable using midazolam or fentanyl (96.1% somewhat or very comfortable), and least comfortable administering etomidate and ketofol (36.5% and 23.1% somewhat or very uncomfortable). These differences were magnified with comparison of physicians with CCFP (Certification in The College of Family Physicians) and CCFP(EM) (emergency medicine) designations. Additionally, etomidate's adverse effects were the least astutely recognized (19%), compared with midazolam combined with fentanyl (63%). CONCLUSION: Physicians practising in nontertiary EDs used more often, remained more comfortable with and were more familiar with older sedation agents than newer agents.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.004 | 0.000 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".